Abstract: Gas-phase chemical mechanisms are a critical part of Chemical Transport Models (CTM), transforming the emissions and chemical reactions in the atmosphere into the corresponding change in the species for modeling O3, PM2.5, and SOAs concentrations. Two of the main chemical mechanisms are the Carbon Bond Mechanisms (CBM) and SAPRC model, which lumps VOCs by chemical groups. Despite the simplicity, the lumping process might induce biases into computations. Some updates were made to the CBM and SAPRC models to reduce biases, including grouping species with the same molecular. CBM has constantly been updated, but there are still some gaps to fill. In 1984, the CB04 was proposed, a mechanism broadly used in CMAQ and other CTMs. In 2005, it was released CB05, including the grouping of some species like aldehydes, and later, including toluene. In 2010, CB06 brought an update including long-lived and relatively abundant organic species formed by peroxy radical. Between 2010 and 2016, four revisions were made in CB06 to improve the gas-phase mechanisms. Despite continuous improvements, some studies showed that different results can be achieved depending on the chemical mechanism and the species adopted. In practice, VOCs under or overestimations up to 200% were found, provoking biases in the ozone prediction, evidencing the need for improvements in VOCs modeling prediction accuracy. Some works have reported a low correlation between predicted and observed VOCs caused mainly by uncertainties in emission inventories. A strategy to improve the uncertainty of the CTM model simulations is using VOCs online measurement data to find a modeled-to-observed ratio of each VOC, aiming to adjust the emission inventory. For this, accurate online VOC measurements are crucial. In the Metropolitan Region of Greater Vitória, ES, Brazil, the NQUALIAR research group improved a BTEX online analyzer, converting it to a broader VOC analyzer (Gas Chromatography) including the 18 most reactive species in ozone formation potential (MIR scale). The following species were set in the GC: benzene, toluene, ethylbenzene, (o, m, p)-xylene, naphthalene, phenanthrene, anthracene, ethylene, ethyltoluene, pentene, butene, isoprene, diethylbenzene, 1,2,3-trimethylbenzene, and isooctane. The modification of the BTEX analyzer to an OFP-VOC GC analyzer was made following the steps: (i) sampling of the GC-online inlet gas (atmospheric air) using Tenax cartridges; (ii) analysis of the Tenax cartridges using a GC benchtop analyzer; (ii) identification of the OFP species sampled with Tenax and their correspondence with the GC-online chromatograms; (iv) calibration of the GC-online using a standard mixture (White Martins, Deutschland) including the 18 OFP species. The results show a significant improvement in the VOCs monitoring, passing from a BTEX monitoring only to a broader characterization of the major OFP-VOCs in the region, which might provide valuable data for the adjustment of the VOC emissions inventory and a better response of CTM for VOCs and O3 modeling, as demonstrated by some authors in the literature. The modified GC- online can provide data with a time resolution of 15 minutes and a quantification limit of 0.01 ppb. The next step of this work is applying a VOC time series of one year to evaluate its correlation with CMAQ simulations and to assess the reliability of the VOC emissions adjustment using a modeled-to-observed ratio of each species in the O3 simulations.

Keywords: VOCs monitoring data, Gas chromatography, Ozone formation potential, Emission inventories, Chemical transport models.